• Journal of Information Technology Applications and Management
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• v.29 no.3
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• pp.75-93
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• 2022

The purpose of this study is to compare and analyze each government's ICT SME support policies to cope with changes in the ICT ecosystem paradigm. In particular, the core policies and policy trends of the Moon's government are presented through keyword network analysis and cognitive map analysis. As a result, core technologies such as ICT(Information Communication Technology), AI(Artificial Intelligence), Big Data, and 5G, which have high values of betweenness centrality and closeness centrality, are major keywords with high propagation power. The cognitive map analysis shows that the opportunity factors for the 4th industrial revolution are being activated through the ICT infrastructure circulation process, the domestic market circulation process, and the global market circulation process. This study is meaningful in terms of cognitive map analysis and utilization based on scientific analysis.

• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.45-53
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• 2023

This study constructs various scenarios required for landscape lighting; furthermore, a large-capacity general-purpose multifunctional controller is designed and implemented to validate the operation of the various scenarios. The multi-functional controller is a large-capacity general-purpose controller composed of a drive and control unit that controls the scenarios and colors of LED modules and an LED display unit. In addition, we conduct a computer simulation by designing a control system to represent the most appropriate color according to the input values of the temperature, illuminance, and humidity, using the neuro-control system. Consequently, when examining the result and output color according to neuro-control, unlike existing crisp logic, neuro-control does not require the storage of many data inputs because of the characteristics of artificial intelligence; the desired value can be controlled by learning with learning data.

• Earthquakes and Structures
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• v.25 no.1
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• pp.15-26
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• 2023

It is of great importance to assess the residual displacement demand in the performance-based seismic design. In this paper, a hybrid deep learning model for predicting the residual displacement spectra under near-fault (NF) ground motions is proposed by combining the long short-term memory network (LSTM) and back-propagation (BP) network. The model is featured by its capacity of predicting the residual displacement spectrum under a given NF ground motion while considering the effects of structural parameters. To construct this model, 315 natural and artificial NF ground motions were employed to compute the residual displacement spectra through elastoplastic time history analysis considering different structural parameters. Based on the resulted dataset with a total of 9,450 samples, the proposed model was finally trained and tested. The results show that the proposed model has a satisfactory accuracy as well as a high efficiency in predicting residual displacement spectra under given NF ground motions while considering the impacts of structural parameters.

• ETRI Journal
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• v.45 no.6
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• pp.929-938
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• 2023

The detection of all the symbols transmitted simultaneously in multiuser systems using limited wireless resources is challenging. Traditional model-based methods show high performance with perfect channel state information (CSI); however, severe performance degradation will occur if perfect CSI cannot be acquired. In contrast, data-driven methods perform slightly worse than model-based methods in terms of symbol error ratio performance in perfect CSI states; however, they are also able to overcome extreme performance degradation in imperfect CSI states. This study proposes a novel deep learning-based method by improving a state-of-the-art data-driven technique called deep soft interference cancellation (DSIC). The enhanced DSIC (EDSIC) method detects multiuser symbols in a fully sequential manner and uses an efficient neural network structure to ensure high performance. Additionally, error-propagation mitigation techniques are used to ensure robustness against channel uncertainty. The EDSIC guarantees a performance that is very close to the optimal performance of the existing model-based methods in perfect CSI environments and the best performance in imperfect CSI environments.

• Journal of the Korean Society for Railway
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• v.16 no.4
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• pp.278-285
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• 2013

The suppression of residual settlement is required on earthwork sections as concrete track is introduced. Use of pile-slab structure is one of the settlement restraining methods applied on soft ground. The slab distributes the upper embankment load and piles transfer the load from the slab to the stiff ground. While this method is very effective in terms of load transfer, it has not yet been established for dealing with the vibration transfer effects and interaction characteristics between a structure and the ground. It is possible that vibration caused by a moving train load is propagated in the upper embankment, because the slab acts as a reflection layer and waves are multi-reflected. In this present paper, wave propagation generated by a moving train load is evaluated in the time and frequency domains to consider a roadbed structure using an artificial impact load and field measured train load. The results confirmed the wave reflection effect on the pile-slab structure, if the embankment height is sufficient, vibration propagation can be stably restrained, whereas if the height is not sufficient, the vibration amplitude is increased.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.117-129
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• 2008

The cost-based scheduling work has been done in both the Operations Research (OR) and Artificial Intelligence (AI) literature. To deal with more realistic problems, AI-based heuristic scheduling approach with non-regular performance measures has been studied. However, there has been little research effort to develop a full inter-job cost propagation algorithm (CPA) for different jobs having multiple downstream and upstream activities. Without such a CPA, decision-making in scheduling heuristics relies upon local, incomplete cost information, resulting in poor schedule performance from the overall cost minimizing objective. For such a purpose, we need two types of CPAs : intra-job CPA and inter-job CPA. Whenever there is a change in cost information of an activity in a job in the process of scheduling, the intra-job CPA updates cost curves of other activities connected through temporal constraints within the same job. The inter-job CPA extends cost propagation into other jobs connected through precedence relationships. By utilizing the cost information provided by CPAs, we propose cost-based scheduling heuristics that attempt to minimize the total schedule cost. This paper develops inter-job CPAs that create and update cost curves of each activity in each search state, and propagate cost information throughout a whole network of temporal constraints. Also we propose various cost-based scheduling heuristics that attempt to minimize the total schedule cost by utilizing the cost propagation algorithm.

• Korean Journal of Plant Resources
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• v.32 no.4
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• pp.290-295
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• 2019

This study was carried out to select the optimal condition for prothallus propagation and sporophyte formation of Leptogramma pozoi (Lag.) Ching subsp. mollissima (Fisch. ex Kunze) Nakaike and to provide basic data for mass production system. In the propagation, 300 mg of prothallus were inoculated in different kinds of medium [1/4, 1/2, Murashige and Skoog (MS), Knop], sucrose (0, 1, 2, 3, 4%), and cultured for 8 weeks. Sporophyte formation studies were carried out by inoculating blended prothallus into artificial soils. The soils were mixed with horticultural substrate, peatmoss, perlite, and decomposed granite at different ratios or only with the horticultural substrate. Then the prothallus was cultivated for 12 weeks to figure out the formation and growth of the sporophytes. The growth and development of prothalli were excellent on MS medium. According to medium components, prothallus growth was favorable in all treatments except 0% sucrose treatment and the highest in 2% sucrose. In the experiment of soil mixtures, sporophyte formation was the highest in the horticultural substrate:perlite 2:1 (v:v) and horticultural substrate:decomposed granite 2:1 (v:v) treatment, and the overall growth was good in the horticultural substrate:decomposed granite 2:1 (v:v) mixed soil.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.1
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• pp.35-42
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• 2008

In the nuclear power plant, early detection of fatigue crack by non-destructive test (NDT) equipment due to the thermal cyclic load is very important in terms of strict safety regulation. To this end, many efforts are exerted to the fabrication of artificial cracked specimen for practicing engineers in the NDT company. The crack of this kind, however, cannot be made by conventional machining, but should be made under thermal cyclic load that is close to the in-situ condition, which takes tremendous time due to the repetition. In this study, thermal loading condition is investigated to minimize the time for fabricating the cracked specimen using simulation technique which predicts the crack initiation and propagation behavior. Simulation and experiment are conducted under an initial assumed condition for validation purpose. A number of simulations are conducted next under a variety of heating and cooling conditions, from which the best solution to achieve minimum time for crack with wanted size is found. In the simulation, general purpose software ANSYS is used for the stress analysis, MATLAB is used to compute crack initiation life, and ZENCRACK, which is special purpose software for crack growth prediction, is used to compute crack propagation life. As a result of the study, the time for the crack to reach the size of 1mm is predicted from the 418 hours at the initial condition to the 319 hours at the optimum condition, which is about 24% reduction.

• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.721-731
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• 2010

The rainfall-runoff relationship is very difficult to predict because it is complicate factor affected by many temporal and spatial parameters of the basin. In recent, models which is based on artificial intelligent such as neural network, genetic algorithm fuzzy etc., are frequently used to predict discharge while stochastic or deterministic or empirical models are used in the past. However, the discharge data which are generally used for prediction as training and validation set are often estimated from rating curve which has potential error in its estimation that makes a problem in reliability. Therefore, in this study, water stage is predicted from antecedent rainfall and water stage data for short term using three models of neural network which trained by error back propagation algorithm and optimized by genetic algorithm and training error back propagation after it is optimized by genetic algorithm respectively. As the result, the model optimized by Genetic Algorithm gives the best forecasting ability which is not much decreased as the forecasting time increase. Moreover, the models using stage data only as the input data give better results than the models using precipitation data with stage data.

• Journal of Wetlands Research
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• v.23 no.2
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• pp.107-115
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• 2021

In order to analyze wave propagation, tidal current, and sediment transport in the vicinity of the Gaeya open channel, it was classified into before(CASE1W) and after(CASE2W) installation of various artificial structures, and the calculation results for CASE1W and CASE2W were compared. For wave propagation, the results of incident and reflected waves were derived using the SWAN numerical model, and the tidal current velocity results were derived using the FLOW2DH numerical model for tidal current. The results of the SWAN numerical model and the FLOW2DH numerical model became the input conditions for the SEDTRAN numerical model that predicts sediment transport, and the maximum bed shear stress and suspended sediment concentration distribution near the Gaeya open channel were calculated through the SEDTRAN numerical model. As a result of the calculation of the SWAN numerical model, the wave height of CASE2W was increased by 40~50 % compared to CASE1W because the incident wave was diffracted and superimposed and the reflected wave was generated by about 7 km long northen jetty. As a result of the calculation of the FLOW2DH numerical model, According to the northen breakwater, the northen jetty and Geumrando, CASE2W was calculated 10~30 % faster than CASE1W in the tidal current of the Gaeya open channel. As a result of the calculation of the SEDTRAN numerical model, the section where the maximum bed shear stress is 1.0 N/m² or more and the suspended concentration is 80mg/L or more was widely distributed in the Gaeya open channel from the marine environment by the complex wave field(incident wave, reflected wave and tidal wave) and the installation of various artificial structures. it is believed that a sedimentation phenomenon occurred in the Gaeya open channel.